From Gene Annotation to Function Prediction for Metagenomics. Sharifi, F. & Ye, Y. Volume 1611. Methods in molecular biology (Clifton, N.J.), pages 27-34. Humana Press, New York, NY, 2017.
Methods in molecular biology (Clifton, N.J.) [pdf]Paper  Methods in molecular biology (Clifton, N.J.) [link]Website  abstract   bibtex   
Microbes play important roles in almost every aspect of life, including human health and diseases. Facilitated by the rapid development of sequencing technologies, metagenomics research has accelerated the accumulation of genomic sequences of microbial species that had been inaccessible before. Analysis of the metagenomic sequencing data can reveal not only the species but also the functional composition of microbial communities. Here, we report a pipeline for functional annotation of metagenomic datasets. The pipeline is built from several programs that we have developed for metagenomic sequence analysis including a protein-coding gene predictor for short reads (or contigs) and a fast similarity search tool. Given a metagenomic dataset, the pipeline reports putative protein-coding genes (or gene fragments) and functional annotations of the genes in Gene Ontology (GO) terms and Enzyme Commission (EC) numbers, and potential metabolic pathways that are likely encoded by the metagenome. Fun4Me is available for download at .

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